Metadata-Version: 2.1
Name: fastcvapp
Version: 0.2.1
Summary: Create a computer vision app FAST! Multiprocessing made easy, right out of the box.
Home-page: https://github.com/AccelQuasarDragon/FastCVApp
License: MIT
Author: AccelQuasarDragon
Requires-Python: >=3.9.0,<3.12
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Requires-Dist: Kivy (>=2.2.0,<3.0.0)
Requires-Dist: blosc2 (>=2.2.2,<3.0.0)
Requires-Dist: mediapipe (>=0.10.0,<0.11.0)
Requires-Dist: numpy (>=1.23.4,<2.0.0)
Requires-Dist: opencv-python (>=4.6.0.66,<5.0.0.0)
Project-URL: Repository, https://github.com/AccelQuasarDragon/FastCVApp
Description-Content-Type: text/markdown

# Welcome to Fast CV App!

What is Fast CV App? Fast Computer Vision App is a small framework, guide, and examples about running Python code with multiprocessing from start to finish, beginning with `python main.py` and ending with an executable with PyInstaller on Windows and Mac.

Here you will learn know how to sidestep bottlenecks using multiprocessing and shared memory. Fast CV App was inspired by the ease and speed of [FastAPI](https://fastapi.tiangolo.com/), and while the decorator functionality of FastAPI is not available, rest assured that there are tutorials and examples to make a working CV App within 15 minutes. 

# Getting Started (Youtube Link)

[![Watch the video](https://img.youtube.com/vi/YnhHaKEx7pY/maxresdefault.jpg)](https://www.youtube.com/embed/YnhHaKEx7pY)

# See for yourself:


Fast CV App is built on Kivy for the sole purpose of accessing OpenGL methods in Python without having to learn the ins and outs of OpenGL. This makes cross platform a lot more achievable and the same techniques you can learn here are applicable to any framework as long as you have access to a canvas and can update the canvas whenever you want. 

PyInstaller is used to create the Windows and MacOS (M1 chip) files, and associated .spec files are left in for examination. 

#Windows Example:

https://github.com/AccelQuasarDragon/FastCVApp/assets/138998466/372cb252-0a6f-41eb-a05f-ac4302cb1f6b

#Mac M1 Example:

https://github.com/AccelQuasarDragon/FastCVApp/assets/138998466/eab19c82-a179-4346-9c6a-d6d6e3d1e3bf



# Initial setup
# Running examples:

# Creating a simple example
# Community
- [Kivy Discord](https://discord.gg/hve3BMPrDh)
- documentation: readthedocs



- > done
~ > added to todolist
-what FCVA is about (sell)
-fast
-runs on opengl (kivy)
-cross platform: tested with pyinstaller on windows and macOS (m1-silicon)
~images/examples
Initial setup
Running examples:
Creating a simple example
community; 
kivy discord
documentation: readthedocs

